Basic theorem and global exponential stability of differential-algebraic neural networks with delay.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 33915455.
- Also identified by DOI 10.1016/j.neunet.2021.01.017.
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Abstract
A differential-algebraic neural network (DANN) with delay (DDANN) is proposed. Firstly, the global existence and uniqueness theorems are established for a DDANN, respectively. Next, a new differential-algebraic inequality is established. Then, a theorem on global exponential stability of DDANN is shown by using this inequality. As an application of DDANN, a very concise criterion on global exponential stability for a neutral-type neural network is given by using DDANNs. Finally, two examples are given to illustrate the theoretical results.
Medical subject headings
- Neural Networks, Computer